The PPPLOT statement creates a probability-probability plot (also referred to as a P-P plot or percent plot), which compares the empirical cumulative distribution function (ecdf) of a variable with a specified theoretical cumulative distribution function such as the normal. If the two distributions match, the points on the plot form a linear pattern that passes through the origin and has unit slope. Thus, you can use a P-P plot to determine how well a theoretical distribution models a set of measurements.
You can specify one of the following theoretical distributions with the PPPLOT statement:
beta
exponential
gamma
Gumbel
inverse Gaussian
lognormal
normal
generalized Pareto
power function
Rayleigh
Weibull
You can use options in the PPPLOT statement to do the following:
specify or estimate parameters for the theoretical distribution
request graphical enhancements
You can also create a comparative P-P plot by using the PPPLOT statement in conjunction with a CLASS statement.
You have three alternatives for producing P-P plots with the PPPLOT statement:
ODS Graphics output is produced if ODS Graphics is enabled, for example by specifying the ODS GRAPHICS ON statement prior to the PROC statement.
Otherwise, traditional graphics are produced by default if SAS/GRAPH® is licensed.
Legacy line printer charts are produced when you specify the LINEPRINTER option in the PROC statement.
See Chapter 3: SAS/QC Graphics, for more information about producing these different kinds of graphs.
Note: Probability-probability plots should not be confused with probability plots, which compare a set of ordered measurements with percentiles from a specified distribution. You can create probability plots with the PROBPLOT statement.